Dependency Graph Parsing as Sequence Labeling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A8ILE7YJW" target="_blank" >RIV/00216208:11320/25:8ILE7YJW - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217736996&partnerID=40&md5=e1b5484cb473e233a3ea43a24e3af76c" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217736996&partnerID=40&md5=e1b5484cb473e233a3ea43a24e3af76c</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Dependency Graph Parsing as Sequence Labeling

Popis výsledku v původním jazyce

Various linearizations have been proposed to cast syntactic dependency parsing as sequence labeling. However, these approaches do not support more complex graph-based representations, such as semantic dependencies or enhanced universal dependencies, as they cannot handle reentrancy or cycles. By extending them, we define a range of unbounded and bounded linearizations that can be used to cast graph parsing as a tagging task, enlarging the toolbox of problems that can be solved under this paradigm. Experimental results on semantic dependency and enhanced UD parsing show that with a good choice of encoding, sequence-labeling dependency graph parsers combine high efficiency with accuracies close to the state of the art, in spite of their simplicity. © 2024 Association for Computational Linguistics.

Název v anglickém jazyce

Dependency Graph Parsing as Sequence Labeling

Popis výsledku anglicky

Various linearizations have been proposed to cast syntactic dependency parsing as sequence labeling. However, these approaches do not support more complex graph-based representations, such as semantic dependencies or enhanced universal dependencies, as they cannot handle reentrancy or cycles. By extending them, we define a range of unbounded and bounded linearizations that can be used to cast graph parsing as a tagging task, enlarging the toolbox of problems that can be solved under this paradigm. Experimental results on semantic dependency and enhanced UD parsing show that with a good choice of encoding, sequence-labeling dependency graph parsers combine high efficiency with accuracies close to the state of the art, in spite of their simplicity. © 2024 Association for Computational Linguistics.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

EMNLP - Conf. Empir. Methods Nat. Lang. Process., Proc. Conf.

ISBN

979-889176164-3

ISSN

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e-ISSN

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Počet stran výsledku

25

Strana od-do

11804-11828

Název nakladatele

Association for Computational Linguistics (ACL)

Místo vydání

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Místo konání akce

Hybrid, Miami

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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